Acceleration Level Control of Redundant Manipulators with Physical Constraints Compliance and Disturbance Rejection under Complex Environment

Investigation of joint torque constraint compliance is of significance for robot manipulators especially working in complex environments. A lot of which is attributed to that, on the one hand, it is beneficial to the improvement of both safety and reliability of the mission execution. On the other h...
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Autor*in:	Jinglun Liang [verfasserIn] Yisheng Rong [verfasserIn] Guoliang Ye [verfasserIn] Xiaoxiao Li [verfasserIn] Jianwen Guo [verfasserIn] Zhenzhen He [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2020

Übergeordnetes Werk:	In: Complexity - Hindawi-Wiley, 2017, (2020)
Übergeordnetes Werk:	year:2020

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc Journal toc

DOI / URN:	10.1155/2020/8844209

Katalog-ID:	DOAJ062750402

Internformat


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allfields	10.1155/2020/8844209 doi (DE-627)DOAJ062750402 (DE-599)DOAJ0498a6fce82c41379595bf2f2de58d99 DE-627 ger DE-627 rakwb eng QA75.5-76.95 Jinglun Liang verfasserin aut Acceleration Level Control of Redundant Manipulators with Physical Constraints Compliance and Disturbance Rejection under Complex Environment 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Investigation of joint torque constraint compliance is of significance for robot manipulators especially working in complex environments. A lot of which is attributed to that, on the one hand, it is beneficial to the improvement of both safety and reliability of the mission execution. On the other hand, the energy consumption required by the robot to complete the desired mission can be reduced. Most existing schemes do not take the joint torque limit and other inherent physical structure limits in a manipulator into account at the same time. In addition, many unavoidable uncertainties such as the external environmental disturbance and/or electromagnetism interferences in the circuit system may influence the accuracy and effectiveness of the task execution for a robot. In this study, we cast light on the acceleration level control of redundant robot manipulators considering both four physical constraint limits and interference rejection. A robust unified quadratic-programming-based hybrid control scheme is proposed, where the joint torque constraints are converted as two inequality constraints based on the robots’ dynamics equation. A recurrent-neural-network-based controller is designed for solving the control variable. Numerical experiments performing in PUMA 560 manipulator and planer manipulator illustrate that a rational torque distribution is obtained among the joints and the considered physical structural vectors are all restricted to the respective constraint range. In addition, even disturbed by the noise, the manipulator still successfully tracks the desired trajectory under the proposed control scheme. Electronic computers. Computer science Yisheng Rong verfasserin aut Guoliang Ye verfasserin aut Xiaoxiao Li verfasserin aut Jianwen Guo verfasserin aut Zhenzhen He verfasserin aut In Complexity Hindawi-Wiley, 2017 (2020) (DE-627)312897278 (DE-600)2004607-8 10990526 nnns year:2020 https://doi.org/10.1155/2020/8844209 kostenfrei https://doaj.org/article/0498a6fce82c41379595bf2f2de58d99 kostenfrei http://dx.doi.org/10.1155/2020/8844209 kostenfrei https://doaj.org/toc/1076-2787 Journal toc kostenfrei https://doaj.org/toc/1099-0526 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_151 GBV_ILN_161 GBV_ILN_165 GBV_ILN_170 GBV_ILN_171 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2010 GBV_ILN_2014 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2068 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 2020
spelling	10.1155/2020/8844209 doi (DE-627)DOAJ062750402 (DE-599)DOAJ0498a6fce82c41379595bf2f2de58d99 DE-627 ger DE-627 rakwb eng QA75.5-76.95 Jinglun Liang verfasserin aut Acceleration Level Control of Redundant Manipulators with Physical Constraints Compliance and Disturbance Rejection under Complex Environment 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Investigation of joint torque constraint compliance is of significance for robot manipulators especially working in complex environments. A lot of which is attributed to that, on the one hand, it is beneficial to the improvement of both safety and reliability of the mission execution. On the other hand, the energy consumption required by the robot to complete the desired mission can be reduced. Most existing schemes do not take the joint torque limit and other inherent physical structure limits in a manipulator into account at the same time. In addition, many unavoidable uncertainties such as the external environmental disturbance and/or electromagnetism interferences in the circuit system may influence the accuracy and effectiveness of the task execution for a robot. In this study, we cast light on the acceleration level control of redundant robot manipulators considering both four physical constraint limits and interference rejection. A robust unified quadratic-programming-based hybrid control scheme is proposed, where the joint torque constraints are converted as two inequality constraints based on the robots’ dynamics equation. A recurrent-neural-network-based controller is designed for solving the control variable. Numerical experiments performing in PUMA 560 manipulator and planer manipulator illustrate that a rational torque distribution is obtained among the joints and the considered physical structural vectors are all restricted to the respective constraint range. In addition, even disturbed by the noise, the manipulator still successfully tracks the desired trajectory under the proposed control scheme. Electronic computers. Computer science Yisheng Rong verfasserin aut Guoliang Ye verfasserin aut Xiaoxiao Li verfasserin aut Jianwen Guo verfasserin aut Zhenzhen He verfasserin aut In Complexity Hindawi-Wiley, 2017 (2020) (DE-627)312897278 (DE-600)2004607-8 10990526 nnns year:2020 https://doi.org/10.1155/2020/8844209 kostenfrei https://doaj.org/article/0498a6fce82c41379595bf2f2de58d99 kostenfrei http://dx.doi.org/10.1155/2020/8844209 kostenfrei https://doaj.org/toc/1076-2787 Journal toc kostenfrei https://doaj.org/toc/1099-0526 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_151 GBV_ILN_161 GBV_ILN_165 GBV_ILN_170 GBV_ILN_171 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2010 GBV_ILN_2014 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2068 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 2020
allfields_unstemmed	10.1155/2020/8844209 doi (DE-627)DOAJ062750402 (DE-599)DOAJ0498a6fce82c41379595bf2f2de58d99 DE-627 ger DE-627 rakwb eng QA75.5-76.95 Jinglun Liang verfasserin aut Acceleration Level Control of Redundant Manipulators with Physical Constraints Compliance and Disturbance Rejection under Complex Environment 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Investigation of joint torque constraint compliance is of significance for robot manipulators especially working in complex environments. A lot of which is attributed to that, on the one hand, it is beneficial to the improvement of both safety and reliability of the mission execution. On the other hand, the energy consumption required by the robot to complete the desired mission can be reduced. Most existing schemes do not take the joint torque limit and other inherent physical structure limits in a manipulator into account at the same time. In addition, many unavoidable uncertainties such as the external environmental disturbance and/or electromagnetism interferences in the circuit system may influence the accuracy and effectiveness of the task execution for a robot. In this study, we cast light on the acceleration level control of redundant robot manipulators considering both four physical constraint limits and interference rejection. A robust unified quadratic-programming-based hybrid control scheme is proposed, where the joint torque constraints are converted as two inequality constraints based on the robots’ dynamics equation. A recurrent-neural-network-based controller is designed for solving the control variable. Numerical experiments performing in PUMA 560 manipulator and planer manipulator illustrate that a rational torque distribution is obtained among the joints and the considered physical structural vectors are all restricted to the respective constraint range. In addition, even disturbed by the noise, the manipulator still successfully tracks the desired trajectory under the proposed control scheme. Electronic computers. Computer science Yisheng Rong verfasserin aut Guoliang Ye verfasserin aut Xiaoxiao Li verfasserin aut Jianwen Guo verfasserin aut Zhenzhen He verfasserin aut In Complexity Hindawi-Wiley, 2017 (2020) (DE-627)312897278 (DE-600)2004607-8 10990526 nnns year:2020 https://doi.org/10.1155/2020/8844209 kostenfrei https://doaj.org/article/0498a6fce82c41379595bf2f2de58d99 kostenfrei http://dx.doi.org/10.1155/2020/8844209 kostenfrei https://doaj.org/toc/1076-2787 Journal toc kostenfrei https://doaj.org/toc/1099-0526 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_151 GBV_ILN_161 GBV_ILN_165 GBV_ILN_170 GBV_ILN_171 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2010 GBV_ILN_2014 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2068 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 2020
allfieldsGer	10.1155/2020/8844209 doi (DE-627)DOAJ062750402 (DE-599)DOAJ0498a6fce82c41379595bf2f2de58d99 DE-627 ger DE-627 rakwb eng QA75.5-76.95 Jinglun Liang verfasserin aut Acceleration Level Control of Redundant Manipulators with Physical Constraints Compliance and Disturbance Rejection under Complex Environment 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Investigation of joint torque constraint compliance is of significance for robot manipulators especially working in complex environments. A lot of which is attributed to that, on the one hand, it is beneficial to the improvement of both safety and reliability of the mission execution. On the other hand, the energy consumption required by the robot to complete the desired mission can be reduced. Most existing schemes do not take the joint torque limit and other inherent physical structure limits in a manipulator into account at the same time. In addition, many unavoidable uncertainties such as the external environmental disturbance and/or electromagnetism interferences in the circuit system may influence the accuracy and effectiveness of the task execution for a robot. In this study, we cast light on the acceleration level control of redundant robot manipulators considering both four physical constraint limits and interference rejection. A robust unified quadratic-programming-based hybrid control scheme is proposed, where the joint torque constraints are converted as two inequality constraints based on the robots’ dynamics equation. A recurrent-neural-network-based controller is designed for solving the control variable. Numerical experiments performing in PUMA 560 manipulator and planer manipulator illustrate that a rational torque distribution is obtained among the joints and the considered physical structural vectors are all restricted to the respective constraint range. In addition, even disturbed by the noise, the manipulator still successfully tracks the desired trajectory under the proposed control scheme. Electronic computers. Computer science Yisheng Rong verfasserin aut Guoliang Ye verfasserin aut Xiaoxiao Li verfasserin aut Jianwen Guo verfasserin aut Zhenzhen He verfasserin aut In Complexity Hindawi-Wiley, 2017 (2020) (DE-627)312897278 (DE-600)2004607-8 10990526 nnns year:2020 https://doi.org/10.1155/2020/8844209 kostenfrei https://doaj.org/article/0498a6fce82c41379595bf2f2de58d99 kostenfrei http://dx.doi.org/10.1155/2020/8844209 kostenfrei https://doaj.org/toc/1076-2787 Journal toc kostenfrei https://doaj.org/toc/1099-0526 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_151 GBV_ILN_161 GBV_ILN_165 GBV_ILN_170 GBV_ILN_171 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2010 GBV_ILN_2014 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2068 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 2020
allfieldsSound	10.1155/2020/8844209 doi (DE-627)DOAJ062750402 (DE-599)DOAJ0498a6fce82c41379595bf2f2de58d99 DE-627 ger DE-627 rakwb eng QA75.5-76.95 Jinglun Liang verfasserin aut Acceleration Level Control of Redundant Manipulators with Physical Constraints Compliance and Disturbance Rejection under Complex Environment 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Investigation of joint torque constraint compliance is of significance for robot manipulators especially working in complex environments. A lot of which is attributed to that, on the one hand, it is beneficial to the improvement of both safety and reliability of the mission execution. On the other hand, the energy consumption required by the robot to complete the desired mission can be reduced. Most existing schemes do not take the joint torque limit and other inherent physical structure limits in a manipulator into account at the same time. In addition, many unavoidable uncertainties such as the external environmental disturbance and/or electromagnetism interferences in the circuit system may influence the accuracy and effectiveness of the task execution for a robot. In this study, we cast light on the acceleration level control of redundant robot manipulators considering both four physical constraint limits and interference rejection. A robust unified quadratic-programming-based hybrid control scheme is proposed, where the joint torque constraints are converted as two inequality constraints based on the robots’ dynamics equation. A recurrent-neural-network-based controller is designed for solving the control variable. Numerical experiments performing in PUMA 560 manipulator and planer manipulator illustrate that a rational torque distribution is obtained among the joints and the considered physical structural vectors are all restricted to the respective constraint range. In addition, even disturbed by the noise, the manipulator still successfully tracks the desired trajectory under the proposed control scheme. Electronic computers. Computer science Yisheng Rong verfasserin aut Guoliang Ye verfasserin aut Xiaoxiao Li verfasserin aut Jianwen Guo verfasserin aut Zhenzhen He verfasserin aut In Complexity Hindawi-Wiley, 2017 (2020) (DE-627)312897278 (DE-600)2004607-8 10990526 nnns year:2020 https://doi.org/10.1155/2020/8844209 kostenfrei https://doaj.org/article/0498a6fce82c41379595bf2f2de58d99 kostenfrei http://dx.doi.org/10.1155/2020/8844209 kostenfrei https://doaj.org/toc/1076-2787 Journal toc kostenfrei https://doaj.org/toc/1099-0526 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_151 GBV_ILN_161 GBV_ILN_165 GBV_ILN_170 GBV_ILN_171 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2010 GBV_ILN_2014 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2068 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 2020
language	English
source	In Complexity (2020) year:2020
sourceStr	In Complexity (2020) year:2020
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Electronic computers. Computer science
isfreeaccess_bool	true
container_title	Complexity
authorswithroles_txt_mv	Jinglun Liang @@aut@@ Yisheng Rong @@aut@@ Guoliang Ye @@aut@@ Xiaoxiao Li @@aut@@ Jianwen Guo @@aut@@ Zhenzhen He @@aut@@
publishDateDaySort_date	2020-01-01T00:00:00Z
hierarchy_top_id	312897278
id	DOAJ062750402
language_de	englisch
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callnumber-first	Q - Science
author	Jinglun Liang
spellingShingle	Jinglun Liang misc QA75.5-76.95 misc Electronic computers. Computer science Acceleration Level Control of Redundant Manipulators with Physical Constraints Compliance and Disturbance Rejection under Complex Environment
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topic_title	QA75.5-76.95 Acceleration Level Control of Redundant Manipulators with Physical Constraints Compliance and Disturbance Rejection under Complex Environment
topic	misc QA75.5-76.95 misc Electronic computers. Computer science
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title	Acceleration Level Control of Redundant Manipulators with Physical Constraints Compliance and Disturbance Rejection under Complex Environment
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title_full	Acceleration Level Control of Redundant Manipulators with Physical Constraints Compliance and Disturbance Rejection under Complex Environment
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author_browse	Jinglun Liang Yisheng Rong Guoliang Ye Xiaoxiao Li Jianwen Guo Zhenzhen He
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title_sort	acceleration level control of redundant manipulators with physical constraints compliance and disturbance rejection under complex environment
callnumber	QA75.5-76.95
title_auth	Acceleration Level Control of Redundant Manipulators with Physical Constraints Compliance and Disturbance Rejection under Complex Environment
abstract	Investigation of joint torque constraint compliance is of significance for robot manipulators especially working in complex environments. A lot of which is attributed to that, on the one hand, it is beneficial to the improvement of both safety and reliability of the mission execution. On the other hand, the energy consumption required by the robot to complete the desired mission can be reduced. Most existing schemes do not take the joint torque limit and other inherent physical structure limits in a manipulator into account at the same time. In addition, many unavoidable uncertainties such as the external environmental disturbance and/or electromagnetism interferences in the circuit system may influence the accuracy and effectiveness of the task execution for a robot. In this study, we cast light on the acceleration level control of redundant robot manipulators considering both four physical constraint limits and interference rejection. A robust unified quadratic-programming-based hybrid control scheme is proposed, where the joint torque constraints are converted as two inequality constraints based on the robots’ dynamics equation. A recurrent-neural-network-based controller is designed for solving the control variable. Numerical experiments performing in PUMA 560 manipulator and planer manipulator illustrate that a rational torque distribution is obtained among the joints and the considered physical structural vectors are all restricted to the respective constraint range. In addition, even disturbed by the noise, the manipulator still successfully tracks the desired trajectory under the proposed control scheme.
abstractGer	Investigation of joint torque constraint compliance is of significance for robot manipulators especially working in complex environments. A lot of which is attributed to that, on the one hand, it is beneficial to the improvement of both safety and reliability of the mission execution. On the other hand, the energy consumption required by the robot to complete the desired mission can be reduced. Most existing schemes do not take the joint torque limit and other inherent physical structure limits in a manipulator into account at the same time. In addition, many unavoidable uncertainties such as the external environmental disturbance and/or electromagnetism interferences in the circuit system may influence the accuracy and effectiveness of the task execution for a robot. In this study, we cast light on the acceleration level control of redundant robot manipulators considering both four physical constraint limits and interference rejection. A robust unified quadratic-programming-based hybrid control scheme is proposed, where the joint torque constraints are converted as two inequality constraints based on the robots’ dynamics equation. A recurrent-neural-network-based controller is designed for solving the control variable. Numerical experiments performing in PUMA 560 manipulator and planer manipulator illustrate that a rational torque distribution is obtained among the joints and the considered physical structural vectors are all restricted to the respective constraint range. In addition, even disturbed by the noise, the manipulator still successfully tracks the desired trajectory under the proposed control scheme.
abstract_unstemmed	Investigation of joint torque constraint compliance is of significance for robot manipulators especially working in complex environments. A lot of which is attributed to that, on the one hand, it is beneficial to the improvement of both safety and reliability of the mission execution. On the other hand, the energy consumption required by the robot to complete the desired mission can be reduced. Most existing schemes do not take the joint torque limit and other inherent physical structure limits in a manipulator into account at the same time. In addition, many unavoidable uncertainties such as the external environmental disturbance and/or electromagnetism interferences in the circuit system may influence the accuracy and effectiveness of the task execution for a robot. In this study, we cast light on the acceleration level control of redundant robot manipulators considering both four physical constraint limits and interference rejection. A robust unified quadratic-programming-based hybrid control scheme is proposed, where the joint torque constraints are converted as two inequality constraints based on the robots’ dynamics equation. A recurrent-neural-network-based controller is designed for solving the control variable. Numerical experiments performing in PUMA 560 manipulator and planer manipulator illustrate that a rational torque distribution is obtained among the joints and the considered physical structural vectors are all restricted to the respective constraint range. In addition, even disturbed by the noise, the manipulator still successfully tracks the desired trajectory under the proposed control scheme.
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title_short	Acceleration Level Control of Redundant Manipulators with Physical Constraints Compliance and Disturbance Rejection under Complex Environment
url	https://doi.org/10.1155/2020/8844209 https://doaj.org/article/0498a6fce82c41379595bf2f2de58d99 http://dx.doi.org/10.1155/2020/8844209 https://doaj.org/toc/1076-2787 https://doaj.org/toc/1099-0526
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Acceleration Level Control of Redundant Manipulators with Physical Constraints Compliance and Disturbance Rejection under Complex Environment

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